Higher education faculty members incorporate technologies into their teaching and learning practices in higher education for the benefit of their learners. Hence, general technologies, such as presentation software, online classrooms, and learning management systems are ubiquitous in higher education teaching practices. However, emerging…

This study investigates the adoption and usage of artificial intelligence (AI) technologies among Chinese undergraduate accounting students, focusing on the roles of Social Influence (SI), Behavioral Intention (BI), and Actual Usage (AU), while examining the mediating effect of BI and the moderating effect of Voluntariness of Use (VOU). By…

Using pre-service teachers' (PSTs) technological, pedagogical, content knowledge (TPACK) survey responses, this study's cluster analysis identified five distinct learning profiles: Pedagogical Content Knowledge Specialists, Technological Forerunners, Pedagogically Minded, Balanced Integrators, and TPACK Lingerers. Instead of using a single…

This study examines the factors influencing preservice teachers' (PSTs) technology integration during teaching practice in teacher preparation programs. Utilizing a multidimensional framework, the study integrates models such as TPACK, UTAUT, and the Triple-E evaluation rubric, among others. The research involved a Qualtrics survey of 1,217 PSTs…

This study uses one-step meta-analytic structural equation modelling to delve into the technology acceptance model's (TAM) application within education, assessing perceived usefulness, ease of use, intentions to use, and actual technology use. It synthesises previous findings to validate the TAM's effectiveness and uncover the model's predictive…

The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators and institutions have embraced AI and generative AI (GenAI), other individuals remain cautious. This systematic literature review explored teaching…

Artificial Intelligence (AI) is driving ecological shifts and systemic reforms in education. As practitioners of educational reform, teachers' behavioral intention to experience and accept the effectiveness of AI technologies will affect the quality of educational change. From an educational ecology perspective, this study explores the impact of…

The growing popularity of interpreting technology in the industry has raised awareness of incorporating it into interpreter education. However, it is unclear what factors may contribute to students' behavioral use and the consequent effects of using it. With the addition of three external factors (motivation, task-technology fit, and technology…

This non-experimental quantitative study investigated medical school faculty members' behavioral intention to use and actual usage behavior of technology in inquiry-based learning activities in medical schools in the United States by applying the unified theory of acceptance and use of technology (UTAUT). In medical education, situational problems…

The emergence of wearable technologies, including smartwatches, has received a considerable attention from scholars across several sectors. However, there is a scarcity of knowledge regarding the determinants affecting the adoption of these wearables in education. Therefore, this research aims to propose a theoretical research model through the…

This study contributes to the extant literature on instructional technology by investigating the relationships between the social and personal factors and behavioral intention to use virtual reality. Moreover, the current study examined the links between perceived characteristics of virtual reality and attitude and the moderating role that can be…

This study aims to identify factors that can influence students when using the learning management system (LMS) in learning educational pedagogy. The LMS that we mean in this study is Pedagogi.id Platform. The design model in the study uses the UTAUT model. Questionnaires with five UTAUT variables, namely performance expectancy, effort expectancy,…

Adapting the Technology Acceptance Model (TAM) framework, this study investigates English teachers' perspectives on the intention to adopt and integrate ChatGPT in their classrooms. This study utilizes quantitative cross-sectional research with 114 respondents answering the online questionnaire. The Structural Equation Modeling (SEM) statistical…

Higher education has seen substantial changes with the growing integration of computer-based intelligence technologies into the learning process. Nevertheless, the acceptance of computer-based intelligence in advanced educational settings is still faced with various difficulties, including perceived dangers, implementation assumptions, and…

This paper reports on literature related to the assessment of barriers to educational technology assessment. It surveys the development of technology acceptance models from social cognitive theory and innovation diffusion theory through to a unified theory that considers performance expectancy, effort expectancy, and social influence. Because risk…